Applied AI Engineer
WorkOS is hiring an Applied AI Engineer for a remote role open to applicants in United States. It pays $175k-$275k a year and Level rates it ; you can apply on WorkOS.
Level's read on this job
- On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include OpenAI, Perplexity and Cursor.
- Level lists 27 other open roles at WorkOS.
AI in this role
About WorkOS 🚀
WorkOS builds modern developer tools and APIs that make it easy for companies to become Enterprise Ready. Our platform powers authentication, identity, authorization, and other critical infrastructure that developers need to securely scale their products to large organizations.
We recently raised a $100M Series C, valuing the company at $2B, led by Meritech and Sapphire with participation from Greenoaks, Craft, Abstract, and Audacious. WorkOS powers enterprise features for many of the fastest-growing AI companies, including OpenAI, Cursor, and Perplexity, Sierra, and Plaid.
As AI reshapes software, WorkOS is at the frontier of Human and Agent Authentication, Identity, and Access Control helping companies answer a new critical question: who are your agents, and what are they allowed to do? Our fast-growing customer base includes hundreds of modern software companies building the next generation of enterprise-ready products.
About the Role
We're growing our Applied AI team to dramatically increase productivity across Engineering, Sales, Support, and Operations, and to ship AI-powered products that customers rely on directly.
As an Applied AI Engineer, you'll design and ship production AI systems that change how WorkOS builds, sells, supports, and scales. You’ll also be building things that WorkOS customers use, and systems that the entire company depends on daily.
You'll work on a small, high-ownership team that:
Chooses problems based on measurable impact
Moves from idea → prototype → production in days or weeks
Ships at both layers: internal leverage and customer-facing product
Adapts quickly as models, tools, and best practices evolve
This is a 0→1 role with company-wide visibility.
What you'll do
Design and ship customer-facing AI products like ask.workos.com, AI support bots embedded in customer Slack channels, and new surfaces we haven't built yet
Build internal tools that become part of people's daily work: agents, automations, and workflows that are stable, observable, and easy to maintain
Work on big bets: a unified bot framework, a sandboxed coding harness agent, and infrastructure that lets the entire company ship
Use LLMs, embeddings, retrieval, and tool-calling to plug into docs, Slack, GitHub, CRM, analytics, support systems, and internal services
Replace repetitive, multi-step manual processes with orchestrated, AI-driven flows that span multiple apps and data sources
Stay current on new models and tooling, run focused experiments, and help the team converge on patterns, libraries, and infrastructure that compound over time
Example problems you might work on
A sandboxed coding harness that can safely take a bug report or feature spec all the way to a deployed change
A unified bot framework that powers every AI touchpoint, internal and customer-facing from a single, observable backbone
A GTM intelligence layer that gives reps live account context, meeting prep, and follow-up from CRM, product usage, and conversation history
Turning noisy, cross-tool workflows (tickets, Slack threads, docs) into a single agent that handles triage, routing, and suggested actions
Infrastructure that lets any WorkOS team ship a reliable internal AI app without reinventing the stack
What we're looking for
You've taken AI-powered systems from idea to production and through at least one iteration cycle with real users
Strong engineering fundamentals. You're comfortable owning services, data flows, and integrations end-to-end
Experience building with LLM APIs
You think about failure modes, observability, and ownership, not just whether the demo works
Bias toward action. You care less about the model and more about removing real bottlenecks, saving hours, or unlocking workflows the company couldn't do before
Comfort with ambiguity and fast change. The problem, the tools, and the "right" patterns are all evolving, you're excited to help define them
Nice to have
Prior work on customer-facing AI products
Experience with embeddings, retrieval/RAG architectures, and structured tool-calling or agents
Exposure to MCP or similar protocols for connecting AI agents to real systems
Benefits and Perks (US Only) 💖
At WorkOS, we offer resources that emphasize personal and familial well-being. We offer healthcare coverage for you and your family, including medical, dental, and vision. We offer parental leave, paid-time off and fully remote working arrangements.
401k matching
Competitive Equity
Healthcare, dental and vision coverage
FSA, ST/LT Disability, Voluntary Life
Carrot fertility benefits
20 days paid vacation + 10 holidays + unlimited sick leave
12 weeks fully paid parental leave
Fitness: Monthly stipend for gyms, yoga classes, race registrations or whatever keeps you active
Wellness: Monthly stipend for a massage, meditations class, therapy, or activities that enhance your well-being
Commuter benefits for hybrid employees in SF/NYC
Unlimited token usage!
Please inquire directly with our recruiting team for benefits available to those working outside the US.
Equal Opportunity Employer
WorkOS is an equal opportunity employer, committed to diversity and inclusiveness. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
How we rate this
Applied AI Engineer at WorkOS rates 88 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- This job starts at
- $175k
- Typical AI engineer job
- $185k
This posting starts 5% below the typical AI engineer job. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used Perplexity hands-on?
- Walk me through how you've used Cursor in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, OpenAI, Perplexity, and Cursor. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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